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Archive custom dataset

archive_custom_data
Destructive

Archive a custom-data dataset by ID. It goes to the archive, not away — list_archive shows it and restore_from_archive brings it back.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCustom-data ID (from list_custom_data)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoConfirmation that the dataset was archived. Widgets still pointing at it fall back to demo data.
successYesTrue when the call succeeded. A failure comes back as an error result instead.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark destructiveHint=true, but the description adds crucial context beyond that: it clarifies the action is reversible ('goes to the archive, not away') and explicitly names the tools that reverse or display it. This extra behavioral disclosure is valuable and does not contradict the destructive hint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short, front-loaded sentences with zero redundancy. The action is stated first, and the clarifying clause about reversibility is concise and directly relevant. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, single-parameter archive operation, the description fully addresses what the agent needs: it explains the permanent-vs-archived nature, points to related tools for listing and restoring, and is sufficient given the low complexity and available annotations and output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'id' is fully described in the schema (from list_custom_data). The description adds no additional meaning beyond what the schema provides, so the baseline of 3 is appropriate given 100% schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Archive'), a clear resource ('custom-data dataset by ID'), and distinguishes the action from deletion with 'not away'. It clearly differentiates from sibling archive_* tools by focusing on custom data, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by mentioning list_archive and restore_from_archive as complementary tools, signaling that this is the reversible archiving step. However, it does not explicitly state when to use this over other tools (e.g., delete_custom_data is not listed), but the 'not away' phrasing gives a clear hint that it is non-destructive in the long term.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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